The World Wide Web or Internet is a global resource with an abundance of content and information created by people across the globe, herein referred to as “users”. User submitted content can be found on several different social media platforms, Web sites, social media networks, and other Web sources that are publicly available on the Web. Examples of particular social media platforms, which provide a mechanism for users to submit content, include Twitter™, Facebook™, and Pinterest™, which are examples of micro-blog, content, and image sharing platforms. Users of such social media platforms can post a message, micro-blog message, or image, herein referred to as a “post” for others to read, view, respond to, and share. For example, the Twitter™ social media platform currently supports more than 100 million users and over 400 million posts (i.e., Tweets) per day. With such social media platforms containing such a vast amount of user-generated content, data from a social media platform can be a valuable resource for determining public sentiment relating to various issues, topics, people, or companies.
Many people are interested in analyzing such social media content available on the Web, particularly content created by user activity on social media sites, such as, for example, Twitter™, Facebook™, and Pinterest™. One particular example of a set of users who may be interested in such analysis is stock market traders, who generally have an interest in the public sentiment of companies or other financially impactful information. Many solutions are currently available to monitor online content, such as basic Web aggregation software, but these solutions fail to measure the real time public sentiment of social media users. For example, a search can be performed using key words that analysts are interested in, creating a simple count of key word mentions on social media platforms. The amount of mentions can provide a basic measurement of interest, and a large number of key word mentions can determine a high interest in a topic, but there is little context for this amount in regards to time or rate of increase. While this known approach has been conducted in prior art and is commonly used today, modern social media sites provide more mechanisms for sharing information. Social media sites often provide a mechanism to re-post content from users, or to copy and republish the same content that interests them. For example, Twitter™ provides a mechanism to re-post user-submitted content through a mechanism coined as a “Retweet”. A Retweet is created by a Tweet that has been posted on the social media platform Twitter™. The Tweet can then be read by another Twitter™ user, who can then re-post the Tweet based on the user's interest in the Tweet. In other words, the same short message that has been posted by a user can be re-posted by a different user, which is called a Retweet. Retweets can continue to be re-posted by additional users to create an expanding content base of Retweets of the same message.
In another example, Facebook™ provides a mechanism to re-post the user-submitted content through a mechanism coined a “Like”. A Like creates a connection between the posted content on the social networking site Facebook™ and a different user who likes or affirms a person's posted content. In another example, Pinterest™ provides a mechanism to re-post the user-submitted content through a mechanism coined a “Re-pin”. Users can browse others posts for images and “Re-pin” images to their own account.
Simply mentioning a specific area of interest does not provide sufficient information to fully articulate public perception of a topic. For example, a user can mention a certain word such as “Factories” in a message, and several users can mention the same word “Factories”, but counting how many times the word factories is mentioned will not provide information greater than the information present at hand (e.g., factories mentioned X number of times).
Accordingly, what would be desirable is a method that can determine the public sentiment attribute of a post. Moreover, due to the widespread use of social networking sites such as, for example, Twitter™, Facebook™, and Pinterest™, the public sentiment of issues, a company, or any other area of interests may be measured using the methods described herein.
While simply counting the number of posts containing significant key words would provide some measure of public sentiment, what would be desirable is a method that provides a more complex measure of the growth and expansion of re-posts of a message or an image.